The following is a selected excerpt of Chapter 2 from 21st Century Game Design (ISBN 1-58450-429-3) published by Charles River Media.

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Why
is game design often overlooked as an important factor contributing to
game sales? Perhaps because when most people in development companies
talk about “good game design,” they mean “game design that produced a
game I really like.” This sort of subjective validation of game design
is of no use in business, which thrives on repeatable methods based
around capturing a target audience—the market. Unable to see the profit
resulting from “good design”— especially since many allegedly
well-designed games fail commercially— most businessmen ignore design
entirely.

Design
is not suggested to be the only (or even the primary) factor in the
sales of a game. Marketing, for example, is hugely important in making
a product visible in a crowded market. Similarly, the sales of a game
depend greatly upon the budget for development. A game developed on a
budget of $100,000 should not be expected to achieve sales figures
equivalent to a game developed on a budget of $5,000,000. However,
mechanisms such as word of mouth transmit individual opinions of a
product, opinions that will be swayed by the design content of the
game.

Therefore,
we face a great need to make game design relevant to the business side
of the game development process. Once the ragtag market has stabilized,
we will have plenty of time to pursue the artistic side of game
development, but for the time being, that is a luxury we cannot afford.
We would not see inventive filmmakers like the Coen Brothers were it
not for commercially motivated film makers like Spielberg and
Bruckheimer, because the commercial success of a medium clears the way
for artistic expression, not the other way around.

Demographic Game Design

A
first step is to consider a criteria for success—what is a successful
design? Notions such as elegance, a criteria famously applied to the
design process by Ernest Adams, are great aspirational concepts, but
less useful for business purposes. Systemic production rules, such as
Noah Falstein's “400 Project,” provide neither a success criteria nor
aspiration and are useful mainly as a means of provoking discussion.

The concept of demographic game design is
that game design inherently targets an audience, and therefore the
success criterion for a design is how effectively it satisfies the
needs of that audience. This factor is not directly related to sales
figures and is not intended as a means by which to consider the success
of the game as a whole—only the success of the design. If the target
audience is satisfied by the game (which can be determined by
appropriate sampling techniques), the design can be considered a
success.

However,
before these criteria can be applied we must know the demographics that
are available to be targeted, so the first step in demographic game
design is to study the audience. If the game designer is to act as a
player advocate in the development process—as if they are an elected
politician reflecting the diverse needs of their constituency—they must
first acquire a useful audience model.

A Warning on Statistics

It
has often been said that you can make statistics prove anything you
want, and this is true—provided the people you are talking to lack the
critical faculty to see the flaws in the presented argument.
Nonetheless, statistical principles are a vital part of modern business
and science. Quantum mechanics, which all modern computing depends
upon, is essentially statistical in nature, and even the concept of
“species” is not a Platonic ideal, but a Gaussian distribution of
diverse life forms arranged into clusters, which we choose to term
“species” only by convention.

The
most important thing to remember when dealing with statistics of any
kind is that showing a correlation (a connection between two events,
details, or tendencies) does not prove causality; it is merely a clue
to something interesting. For example, in one famous incident a
statistician found a statistically significant correlation between
babies and storks in Switzerland. Storks were consistently nesting on
houses with newborn children. This fact did not prove that babies were
brought by storks, of course, and on investigation it was discovered
that the houses with newborn babies were kept warmer than other houses.
This extra warmth attracted the storks. The lesson is that statistical
correlations tell you nothing of the underlying causal mechanisms.

The
other important aspect of statistics is that statistical data about a
group tells you nothing about individuals in that group. For example,
it is well known that the majority of college students drink alcohol,
but this statistic does not allow you to know whether any given college
student drinks alcohol. Reasoning about the general tells you nothing
about the specific. The advantage of statistics is that whatever does
not average itself out to insignificance in a given set of data is a
tendency that can be counted on. For example, statistical analysis has
demonstrated to the movie industry that roughly 50% of the audience of
a profitable film return to see a sequel, allowing for strategies
involving producing cut-price sequels for short-term gain.

Market Clusters And Audience Models

The notion of a market cluster (or market segment)
originates in marketing. In recent years, with the advent of
narrowcasting channels such as specialist TV stations and personal
e-mail, cluster analysis has fallen out of favor in marketing, but the
technique still has value in other disciplines. The basic principle is
to analyze a data set containing information on a particular group of
people and look for common traits that when taken together define a
coherent group or cluster.

For
example, the vacation travel market identified three distinct clusters:
the demanders, whose priorities are exceptional service; the escapists,
who want to get away and relax; and the educationalists, who want to
see new things, experience new cultures, and so forth. These categories
emerged from a cluster analysis on data taken from a pool of vacation
makers; this data was then sorted by a clustering procedure. Note that
the categories were named after the cluster analysis—the names were created to capture the feel of an abstract cluster of people who shared some common traits.

This
cluster analysis approach is one of the more formal ways of producing
an audience model, but a simpler method exists that anyone can apply:
observation and hypothesis. In essence, you observe many different
people from the audience (or look at statistical data in general) and
draw a hypothesis from the observation. In science, this would be
followed with an attempt to validate the hypothesis. Alas, in the games
industry, many hypotheses are treated as a priori facts. However,
provided you remember that such a hypothesis is only a working
assumption and needs to be tested to determine its value, we find nothing wrong with building an audience model in this way.

Hardcore and Casual Split

This
is the most basic audience model at use in the games industry today. It
is in essence a consensual hypothesis—that is, a hypothesis which the
majority accept as factual—and almost all people working in the games
industry know what is meant by the Hardcore (or Core) market and the Casual market.
Some data at use in the industry might confirm this split, but since no
formal definition for each group exists, it remains in essence a
hypothetical model.

The essence of Hardcore players can be summarized as follows:

Buy and play a lot of games

Game literate (that is, familiar with the conventions of current games)

Play games as a lifestyle preference or priority

Turned on by challenge

Can be polarized—that is, a large proportion can be made to buy the same title

Capcom characterized the Hardcore approach at the start of Resident Evil on
the GameCube (Capcom, 2002) as “Mountain climbing.” This ego-neutral
characterization was used at the start of the game to determine which
players were Hardcore in their approach and therefore required greater
challenge. Selecting this option ran the game at a higher difficulty
level.

On the other hand, Casual players can be summarized as follows:

Play few games—but might play them a lot

Little knowledge about game conventions

Play to relax, or to kill time (much as most people view TV or movies)

Looking for fun or an experience Inherently disparate—cannot easily be polarized

Capcom characterized the Casual approach in the GameCube Resident Evil as
“Hiking.” Players who selected this option played the game at an easier
setting, allowing them to have more fun and enjoy the experience
without the greater emphasis on challenge (which often equates to
greater emphasis on repeated failure). The full wording of the sorting
question at the start of this game is as follows:

Question: Which best describes your opinion about games?

I. MOUNTAIN CLIMBING—Beyond the hardships lies accomplishment.

II. HIKING—The destination can be reached rather comfortably.

The
value of this somewhat unusual question over a straight choice between
“Easy” and “Normal ” (or “Easy” and “Difficult”; or “Normal ” and
“Difficult”) is psychological. A Hardcore player faced with “Easy”
versus “Normal” will pick “Normal,” but a Casual player is equally
likely to pick “Normal,” thinking that choosing “Easy” makes them
deficient in some way. The choice between “Normal” and “Difficult” is
likely to cause some Hardcore players to select “Normal” (on the
grounds that “Difficult” settings are for replay value) and then
complain that the game is too easy. Finally, a choice between “Easy”
and “Difficult” is likely to mislead both Casual and Hardcore types as
they try to decide which of these two options is the normal setting.

In
principle, the advantages of this approach are that tailoring the
gameplay to the audience—and sorting the audience correctly—improves
the reception of the game, equating to stronger sales. Unfortunately
for Resident Evil on the GameCube, the slow-burning sales of
the platform somewhat interfered with the actual unit sales. However,
informal observation shows that Hardcore players were satisfied with
the degree of challenge they received in “Mountain climbing” mode,
while Casual players had no difficulty completing the game in “Hiking”
mode.

This
example clearly shows the value that even a simple audience model can
have when used to approach the design process. The sorting question was
a novel approach, and although it provoked some confusion in
game-literate reviewers, the basic approach seems sound and could be
refined to a more subtle approach.